Query 20+ Years of Global Financial Market Data

Alpha Vantage Market Data provides a request workflow for global financial and economic information. Its scope includes equity time series, options, foreign exchange, cryptocurrency, commodities, economic indicators, and technical indicators. The skill connects these categories to API function names and Python response handling so a data request can be built around the specific series or report needed.

Stock examples retrieve a latest quote, daily OHLCV history, a company overview, and an income statement. Other examples request daily cryptocurrency data, annual GDP, and a relative-strength indicator. Fundamentals coverage also includes ETF profiles, balance sheets, cash flow, earnings, dividends, and splits. Additional intelligence functions cover news sentiment, earnings-call transcripts, gainers and losers, insider transactions, and fixed-window analytics.

Use the skill when a task needs structured market or economic data from Alpha Vantage. Match the requested function to the analytical question: a current quote, historical prices, company reporting, a currency pair, or an economic series have different inputs and output structures. Its scope is data retrieval, with environment-specific validation and expert review still required for downstream work.

Batch requests must respect the applicable account limits. The workflow distinguishes restricted free access from premium plans with broader limits and real-time or intraday access. An HTTP 429 response indicates a exceeded request limit. Add delays when processing multiple symbols, and inspect API responses rather than assuming every successful transport response contains usable market data.

The required input is an Alpha Vantage API key supplied through ALPHAVANTAGE_API_KEY. Each request also selects a function and any relevant symbol, market, interval, series type, or period. Requests go to the query endpoint, with the function name, key, and parameters passed through the requests library.

Common controls include outputsize for compact or full history, datatype for JSON or CSV, and adjusted for split or dividend adjustments. Compact history covers the latest one hundred points. Supported interval choices range from minute-based series to daily, weekly, and monthly values, depending on the endpoint.

Outputs follow function-specific response structures. Quote parsing selects the price field, daily-history parsing selects the time-series object, company overview parsing reads financial measures, and income-statement parsing selects annual reports. Error handling checks Error Message, Note, and Information fields for failures, limit warnings, or API information before using the result.

The Python setup uses requests and pandas. The supplied installation command is:

uv pip install requests pandas

Technical-measure coverage includes moving averages, MACD, RSI, Bollinger bands, stochastic measures, ADX, ATR, OBV, and VWAP. Economic functions include GDP, Treasury yields, the federal funds rate, consumer prices, inflation, unemployment, and payrolls. Forex and cryptocurrency functions include exchange rates and historical series.

For complex multi-step research or persistent workflows, the skill presents K-Dense Web as an optional platform from the same creators. That option accompanies broader analysis rather than changing the lightweight request-and-response workflow.